Published January 2010
| Version v1
Journal article
Learning spectrum's selection in OLAM network for analysis cement samples
Creators
- 1. Institute of Nuclear Science and Technology of Sichuan University, Chengdu of Sichuan Prov (China)
Description
It uses OLAM artificial neural network to analyze the samples of cement raw material. Two kinds of spectrums are used for network learning: pure-element spectrum and mix-element spectrum. The output of pure-element method can be used to construct a simulate spectrum, which can be compared with the original spectrum and judge the shift of spectrum; the mix-element method can store more message and correct the matrix effect, but the multicollinearity among spectrums can cause some side effect to the results. (authors)
Additional details
Publishing Information
- Journal Title
- Nuclear Electronics and Detection Technology
- Journal Volume
- 30
- Journal Issue
- 1
- Journal Page Range
- p. 70, 93-95
- ISSN
- 0258-0934
INIS
- Country of Publication
- China
- Country of Input or Organization
- China
- INIS RN
- 42103707
- Subject category
- S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY;
- Descriptors DEI
- CEMENTS; DATA ANALYSIS; LEARNING; NEURAL NETWORKS; RAW MATERIALS; SPECTRA; SPECTRA UNFOLDING; X-RAY FLUORESCENCE ANALYSIS
- Descriptors DEC
- BUILDING MATERIALS; CHEMICAL ANALYSIS; DATA PROCESSING; MATERIALS; NONDESTRUCTIVE ANALYSIS; PROCESSING; X-RAY EMISSION ANALYSIS
Optional Information
- Notes
- 2 tabs., 8 refs.